Abstract

This website explores inequalities in incarceration patterns within the United States. Analyses have been conducted using incarceration data collected by the Vera Institute, an advocacy and research group focused on transforming American criminal legal and immigration systems. The Vera Institute is particularly interested in ending mass incarceration and reforming our systems to be more just and fair for people of color and other marginalized groups. As such, the following report will focus on revealing patterns of racial inequality and over-incarceration within the United States.

Section 1: Introduction

The aim of this data project is to reveal injustices within United States incarceration trends. To accomplish this goal, I will utilize data from the Vera Institute that contains demographic information and jail population data at the county-level for all 50 states. More specifically, I aim to reveal patterns of racial inequality in incarceration rates, as well as highlight differences in incarceration patterns between states.

The United States is home to the largest incarcerated population in the world. The over-policing and incarceration of people of color has been well documented, and has become a major topic in recent years as part of the resurgence of the Black Lives Matter movement. As it stands, the U.S. criminal justice system targets already vulnerable individuals and communities, and works to perpetuate poverty and racial disparites in wealth and health. Addressing inequalities within the criminal legal system in the United States is necessary for creating a more just world.

I want to acknowledge that the real-world data I am using for my analysis represents the lives of hundreds of thousands of individuals, plus their families and their communities who have been affected by incarceration. I want to honor the hardships and emotions that were involved in becoming a data point in the dataset that I am utilizing. As such, I will ground my work in the values described below, as well as acknowledging those who may be implicated (both directly and indirectly) in my analysis.

Section 2: Data Summary

In this section I will summarize the key findings for each of the remaining 4 sections of my report. In Section 3 I was tasked with creating a bar chart that shows the total jail population of the United States by year, from 1970-2018. Through my analysis, I found that the largest increase in the incarcerated population was in 1989. Additionally, I found that the incarcerated population reached its peak in 2008.

In Section 4 I examined growth trends of the incarcerated population by state. In my graph, I highlighted differences in state-level incarceration rates in Florida, New York, New Hampshire, Maine, Washington and Michigan. I conducted additional analyses that found that the largest incarcerated population was located in CA in the year 2014, with a total of 8.406944^{4} individuals in jail.

In Sections 5 & 6 I began to reveal patterns of inequality in the incarceration data, focusing primarily on differences between incarceration rates of Black and White Americans. In Section 5, I chose to compare the representation of both Black and White Americans in jails versus their representation in the general population. I achieved this by creating a ratio that calculated [percent in jail/percent in general public]. I found that the maximum ratio for Black individuals occurred in Sheridan County, KS and showed that the population of incarcerated Blacks was 118x greater than the population of free Blacks. In contrast, the maximum ratio for White individuals occured in Aleutians East Borough, AK where the population of incarcerated Whites was only 11x greater than free Whites.

Finally, in Section 6 I created a map that showed the relative risk of being incarcerated for Black and White Americans at the county-level. Through my analysis I found that the median relative risk across all US counties was 3.3718582. This value means that when looking at the US as a whole, Black Americans were at around 3.4x the risk of being incarcerated compared to White Americans. You will be able to assess differences in the relative risk of incarceration in more detail in Section 6.

Section 3: Growth of the Prison Population

This graph shows the growth of the total population of all jails in the United States between the years 1970 and 2018. One can note that the jail population was quite stable through the 1970’s, hovering around 150,000 individuals. In the early 1980s, the U.S. jail population begins a steap and steady incline. The population continues to grow into the 2000s, reaching its peak of almost 800,000 individuals in 2008. Since then, the U.S. jail population has decreased slightly, with the most recent counts standing at around 750,000 individuals.

Section 4: Growth of Prison Population by State

This graph shows the growth of jail populations by state. This allows viewers to detect differences in the size of jail populations at the state-level. While the jail population of a particular state may be strongly related to overall population size, comparing states with similar overall population sizes helps to reveal differential patterns in incarceration rates. I’ve chosen to display both New York and Florida on this graph, which have very similar population sizes. However, Florida’s jail population is almost double that of New York. On the other hand, two smaller states of almost equal size: New Hampshire and Maine have almost identical jail population sizes and growth trends. Washington and Michigan have high-to-mid range population sizes, and their jail populations appear to be roughly proportional.

Section 5: Comparing the Representation of Black and White Individuals in Jail vs. the General Population

The above plot seeks to answer the question: Are certain racial groups over-represented in jail populations compared to others? To answer this question, I have created a scatterplot that compares the representation of Black and White people in jail versus their representation in the general population. Each dot represents population data from a singular U.S. county in 2018. For simplicity, only Black and White populations are displayed. The BLUE colored dots represent Black population percentages and the RED dots represent White population percentages.

In theory, for any given county the representation of a certain racial group in the general public should align with the representation of that racial group in jail. For example, if Black people make up ~7% of the general population in King County, WA then theoretically they should make up ~7% of the incarcerated population in King County. This means in a world with no racial inequalities in incarceration rates, the two colors of dots should generally cluster in the same way, and should be roughly along the x=y slope (see the diagonal line displayed on the graph). However, this is not what the data reveals. In fact, the data shows that Black individuals tend to cluster above the diagonal line, and White individuals tend to cluster below it. This means that on average, Black individuals are over-represented in jail populations across the U.S. compared to Whites.

Note: the breakdown of general population data by race was only available for ages 15-64. While this is a limitation of the dataset, I believe that

Section 6: Relative Risk of Incarceration in the United States

The above map shows the relative risk of being incarcerated for Black and White Americans in most states comprising the United States. Some states (CT, DE, HI, RI, & VT) were removed because they did not provide the racial breakdown of their jail populations.

Relative risk is a measure that compares the likelihood of a certain outcome (in this case, being incarcerated) across two distinct groups (in this case, Black and White Americans). Relative risk also adjusts for differences in population size. In the context of this project, the relative risk values I’ve calculated serve to highlight differences in likelihood of being incarcerated for Black individuals vs White individuals. Because the relative risk values I calculated were not normally distributed, I have transformed them by taking the natural log of the values. As a result, a relative risk value >0 for a particular state means that Black individuals are more likely to be incarcerated than Whites in that state. A relative risk value <0 means that Whites are more likely to be incarcerated than Black individuals in that state. More specifically, a relative risk value of 3, means Black individuals are 20.0855369 times more likely to be incarcerated compared to Whites in the same state. Interestingly, my analysis showed that all 50 states had RR values >0. This means that across the entirety of the United States (albeit with differences in magnitude and across other sub-levels like county), Black individuals are at a higher risk of being incarcerated compared to Whites.

This source aided me in developing the conceptual model for my map.